The Latitudinal Diversity Gradient (LDG) has fascinated natural historians, ecologists and evolutionary biologists ever since [1] described it about 200 years ago [2]. Despite such interest, agreement on the origin and nature of this gradient has been elusive. Several tens of hypotheses and models have been put forward as explanations for the LDG [2-3], that can be grouped in ecological, evolutionary and historical explanations [4] (see also [5]). These explanations can be reduced to no less than 26 hypotheses, which account for variations in ecological limits for the establishment of progressively larger assemblages, diversification rates, and time for species accumulation [5]. Besides that, although in general the tropics hold more species, different taxa show different shapes and rates of spatial variation [6], and a considerable number of groups show reverse patterns, with richer assemblages in cold temperate regions (see e.g. [7-9]).
Understanding such complexity needs integrating ecological and evolutionary research into the wide temporal and spatial perspectives provided by the burgeoning field of biogeography. This integrative discipline ¬–that traces back to Humboldt himself (e.g. [10])– seeks to put together historical and functional explanations to explain the complex dynamics of Earth’s biodiversity. Different to quantum physicists, biogeographers cannot pursue the ultimate principle behind the patterns we observe in nature due to the interplay of causes and effects, which in fact tell us that there is not such a single principle. Rather, they need to identify an array of basic principles coming from different perspectives, to then integrate them into models that provide realistic –but never simple– explanations to biodiversity gradients such as LDG (see, e.g., [5; 11]). That is, rather than searching for a sole explanation, research on the LDG must aim to identify as many signals hidden in the pattern as possible, and provide hypotheses or models that account for these signals. To later integrate them and, whenever possible, to validate them with empirical data on the organisms’ distribution, ecology and traits, phylogenies, fossils, etc.
Within this context, Meseguer & Condamine [12] provide a novel perspective to LDG research using phylogenetic and fossil evidence on the origin and extinction of taxa within the turtle, crocodile and lizard (i.e. squamate) lineages. By digging into deep time down to the Triassic (about 250 Myr ago) they are able to identify several episodes of flattening and steepening of the LDG for these three clades. Strikingly, their results show similar diversification rates in the northern hemisphere and in the equator during the over 100 Myr long global greenhouse period that extends from the late Jurassic to the Cretaceous and early Neogene. During this period, the LDG for these three groups would have appeared quite even across a mainly tropical Globe, although the equatorial regions were apparently much more evolutionarily dynamic. The equator shows much higher rates of origination and extinction of branches throughout the Cretaceous, but they counteract each other so net diversification is similar to that of the northern hemisphere in all three groups. The transition to a progressively colder Earth in the Paleogene (starting around 50 Myr ago) provokes a mass extinction in the three clades, which is compensated in the equator by the dispersal of many taxa from the areas that currently pertain to the Holarctic biogeographical realm. Finally, during the coldhouse Earth’s climatic conditions of the Neogene only squamates show significant positive diversification rates in extratropical areas, while the diversity of testudines remains, and crocodiles continue declining progressively towards oblivion in the whole world.
Meseguer & Condamine [12] attribute these temporal patterns to the so-called asymmetric gradient of extinction and dispersal (AGED) framework. Here, the dynamics of extinction-at and dispersal-from high latitudes during colder periods increase the steepness of the LDG. Whereas the gradient flattens when Earth warms up as a result of dispersal from the equator followed by increased diversification in extratropical regions. This idea in itself is not new, for the influence of climatic oscillations on diversification rates is well known, at least for the Pleistocene Ice Ages [13], as is the effect of niche conservatism on the LDG [14]. Nevertheless, Meseguer & Condamine’s AGED provides a synthetic verbal model that could allow integrating the three main types of processes behind the LDG into a single framework. To do this it would be necessary to combine AGED’s cycles of dispersal and diversification with realistic models of: (1) the ecological limits to host rich assemblages in the colder and less productive temperate climatic domains; (2) the variations in diversification rates with shifts in temperature and/or energy regimes; and (3) the geographical patterns of climatic oscillation through time that determine the time for species accumulation in each region.
Integrating these models may allow transposing Meseguer & Condamine’s [12] framework into the more mechanistic macroecological models advocated by Pontarp et al. [5]. This type of mechanistic models has been already used to understand the development of biodiversity gradients through the climatic oscillations of the Pleistocene and the Quaternary (e.g. [11]). So the challenge in this case would be to generate a realistic scenario of geographical dynamics that accounts for plate tectonics and long-term climatic oscillations. This is still a major gap and we would benefit from the integrated work by historical geologists and climatologists here. For instance, there is little doubt about the progressive cooling through the Cenozoic based in isotope recording in sea floor sediments [15]. Meseguer & Condamine [12] use this evidence for separating greenhouse, transition and coldhouse world scenarios, which should not be a problem for these rough classes. However, a detailed study of the evolutionary correlation of true climate variables across the tree of life is still pending, as temperature is inferred only for sea water in an ice-free ocean, say earlier half of the Cenozoic [15]. Precipitation regime is even less known. Such scenario would provide a scaffold upon which the temporal dynamics of several aspects of the generation and loss of biodiversity can be modelled. Additionally, one of the great advantages of selecting key clades to study the LDG would be to determine the functional basis of diversification. There are species traits that are well known to affect speciation and extinction probabilities, such as reproductive strategies or life histories (e.g. [16]). Whereas these traits might also be a somewhat redundant effect of climatic causes, they might foster (i.e. “extended reinforcement”, [17]) or slow diversification. Even so, it is unlikely that such a model would account for all the latitudinal variation in species richness. But it will at least provide a baseline for the main latitudinal variations in the diversity of the regional communities (sensu [18]) worldwide. Within this context the effects of recent ecological, evolutionary and historical processes, such as environmental heterogeneity, current diversification rates or glacial cycles, will only modify the general LDG pattern resulting from the main processes contained in Meseguer & Condamine’s AGED, thereby providing a more comprehensive understanding of the geographical gradients of diversity.

References
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[2] Hawkins, B. A. (2001). Ecology's oldest pattern? Trends in Ecology & Evolution, 16, 470. doi: 10.1016/S0169-5347(01)02197-8
[3] Lomolino, M. V., Riddle, B. R. & Whittaker, R. J. (2017). Biogeography. Fifth Edition. Sinauer Associates, Inc., Sunderland, Massachussets.
[4] Mittelbach, G. G., Schemske, D. W., Cornell, H. V., Allen, A. P., Brown, J. M., Bush, M. B., Harrison, S. P., Hurlbert, A. H., Knowlton, N., Lessios, H. A., McCain, C. M., McCune, A. R., McDade, L. A., McPeek, M. A., Near, T. J., Price, T. D., Ricklefs, R. E., Roy, K., Sax, D. F., Schluter, D., Sobel, J. M. & Turelli, M. (2007). Evolution and the latitudinal diversity gradient: speciation, extinction and biogeography. Ecology Letters, 10, 315-331. doi: 10.1111/j.1461-0248.2007.01020.x
[5] Pontarp, M., Bunnefeld L., Cabral, J. S., Etienne, R. S., Fritz, S. A., Gillespie, R. Graham, C. H., Hagen, O., Hartig, F., Huang, S., Jansson, R., Maliet, O., Münkemüller, T., Pellissier, L., Rangel, T. F., Storch, D., Wiegand, T. & Hurlbert, A. H. (2019). The latitudinal diversity gradient: novel understanding through mechanistic eco-evolutionary models. Trends in ecology & evolution, 34, 211-223. doi: 10.1016/j.tree.2018.11.009
[6] Hillebrand, H. (2004). On the generality of the latitudinal diversity gradient. The American Naturalist, 163, 192-211. doi: 10.1086/381004
[7] Santos, A. M. C. & Quicke, D. L. J. (2011). Large-scale diversity patterns of parasitoid insects. Entomological Science, 14, 371-382. doi: 10.1111/j.1479-8298.2011.00481.x
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[10] Humboldt, A. v. (1805). Essai sur la geographie des plantes; accompagné d'un tableau physique des régions equinoxiales. Levrault, Paris.
[11] Rangel, T. F., Edwards, N. R., Holden, P. B., Diniz-Filho, J. A. F., Gosling, W. D., Coelho, M. T. P., Cassemiro, F. A. S., Rahbek, C. & Colwell, R. K. (2018). Modeling the ecology and evolution of biodiversity: Biogeographical cradles, museums, and graves. Science, 361, eaar5452. doi: 10.1126/science.aar5452
[12] Meseguer, A. S. & Condamine, F. L. (2019). Ancient tropical extinctions contributed to the latitudinal diversity gradient. bioRxiv, 236646, ver. 4 peer-reviewed and recommended by PCI Evol Biol. doi: 10.1101/236646
[13] Jansson, R., & Dynesius, M. (2002). The fate of clades in a world of recurrent climatic change: Milankovitch oscillations and evolution. Annual review of ecology and systematics, 33(1), 741-777. doi: 10.1146/annurev.ecolsys.33.010802.150520
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[16] Zúñiga-Vega, J. J., Fuentes-G, J. A., Ossip-Drahos, A. G., & Martins, E. P. (2016). Repeated evolution of viviparity in phrynosomatid lizards constrained interspecific diversification in some life-history traits. Biology letters, 12, 20160653. doi: 10.1098/rsbl.2016.0653
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Ecological specialisation, especially among parasites infecting a set of host species, is ubiquitous in nature. Host specialisation can be understood as resulting from trade-offs in parasite infectivity, virulence and growth. However, it is not well understood how variation in these trade-offs shapes the overall fitness trade-off a parasite faces when adapting to multiple hosts. For instance, it is not clear whether a strong trade-off in one fitness component may sufficiently constrain the evolution of a generalist parasite despite weak trade-offs in other components. A second mechanism explaining variation in specialisation among species is habitat availability and quality. Rare habitats or habitats that act as ecological sinks will not allow a species to persist and adapt, preventing a generalist phenotype to evolve. Understanding the prevalence of those mechanisms in natural systems is crucial to understand the emergence and maintenance of host specialisation, and biodiversity in general.
In their study "Trait-specific trade-offs prevent niche expansion in two parasites", Lievens et al. [1] report the results of an evolution experiment involving two parasitic microsporidians, Anostracospora rigaudi and Enterocytospora artemiae, infecting two sympatric species of brine shrimp, Artemia franciscana and Artemia parthenogenetica. The two parasites were originally specialised on their primary host: A. rigaudi on A. parthenogenetica and E. artemiae on A. franciscana, although they encounter both species in the wild but at different rates. After passaging each parasite on each single host and on both hosts alternatively, Lievens et al. asked how host specialisation evolved. They found no change in specialisation at the fitness level in A. rigaudi in either treatment, while E. artemiae became more of a generalist after having been exposed to its secondary host, A. parthenogenetica. The most interesting part of the study is the decomposition of the fitness trade-off into its underlying trade-offs in spore production, infectivity and virulence. Both species remained specialised for spore production on their primary host, interpreted as caused by a strong trade-off between hosts preventing improvements on the secondary host. A. rigaudi evolved reduced virulence on its primary host without changes in the overall fitness trad-off, while E. artemiae evolved higher infectivity on its secondary host making it a more generalist parasite and revealing a weak trade-off for this trait and for fitness. Nevertheless, both parasites retained higher fitness on their primary host because of the lack of an evolutionary response in spore production.
This study made two important points. First, it showed that despite apparent strong trade-off in spore production, a weak trade-off in infectivity allowed E. artemiae to become less specialised. In contrast, A. rigaudi remained specialised, presumably because the strong trade-off in spore production was the overriding factor. The fitness trade-off that results from the superposition of multiple underlying trade-offs is thus difficult to predict, yet crucial to understand potential evolutionary outcomes. A second insight is related to the ecological context of the evolution of specialisation. The results showed that E. artemiae should be less specialised than observed, which points to a role played by source-sink dynamics on A. parthenogenetica in the wild. The experimental approach of Lievens et al. thus allowed them to nicely disentangle the various sources of constraints on the evolution of host adaptation in the Artemia system.

References

[1] Lievens, E.J.P., Michalakis, Y. and Lenormand, T. (2019). Trait-specific trade-offs prevent niche expansion in two parasites. bioRxiv, 621581, ver. 4 peer-reviewed and recommended by PCI Evolutionary Biology. doi: 10.1101/621581

Polyploidy, which results in the presence of more than two sets of homologous chromosomes represents a major feature of plant genomes that have undergone successive rounds of duplication followed by more or less rapid diploidization during their evolutionary history. Polyploid complexes containing diploid and derived polyploid taxa are excellent model systems for understanding the short-term consequences of whole genome duplication, and have been particularly well-explored in evolutionary ecology (Ramsey and Ramsey 2014, Rice et al. 2019). Many polyploids (especially when resulting from interspecific hybridization, i.e. allopolyploids) are successful invaders (te Beest et al. 2012) as a result of rapid genome dynamics, functional novelty, and trait evolution. The origin (parental legacy) and modes of formation of polyploids have a critical impact on the subsequent polyploid evolution. Thus, elucidation of the genomic composition of polyploids is fundamental to understanding trait evolution, and such knowledge is still lacking for many invasive species.

Genus Ludwigia is characterized by a complex taxonomy, with an underexplored evolutionary history. Species from section Jussieae form a polyploid complex with diploids, tetraploids, hexaploids, and decaploids that are notorious invaders in freshwater and riparian ecosystems (Thouvenot et al.2013).   Molecular phylogeny of the genus based on nuclear and chloroplast sequences (Liu et al. 2027) suggested some relationships between diploid and polyploid species, without fully resolving the question of the parentage of the polyploids. In their study, Barloy et al. (2023) have used a combination of molecular cytogenetics (Genomic In situ Hybridization), morphology and experimental crosses to elucidate the genomic compositions of the polyploid species, and show that the examined polyploids are of hybrid origin (allopolyploids). The tetraploid L. stolonifera derives from the diploids L. peploides subsp. montevidensis (AA genome) and L. helminthorhiza (BB genome). The tetraploid L. ascendens also share the BB genome combined with an undetermined different genome. The hexaploid L. grandiflora subsp. grandiflora has inherited the diploid AA genome combined with additional unidentified genomes. The decaploid L. grandiflora subsp. hexapetala has inherited the tetraploid L. stolonifera and the hexaploid L. grandiflora subsp. hexapetala genomes. As the authors point out, further work is needed, including additional related diploid (e.g. other subspecies of L. peploides) or tetraploid (L.  hookeri and L. peduncularis)  taxa that remain to be investigated, to address the nature of the undetermined parental genomes mentioned above. 

The presented work (Barloy et al.  2023) provides significant knowledge of this poorly investigated group with regard to genomic information and polyploid origin, and opens perspectives for future studies. The authors also detect additional diagnostic morphological traits of interest for in-situ discrimination of the taxa when monitoring invasive populations.  

References

Barloy D., Portillo-Lemus L., Krueger-Hadfield S.A., Huteau V., Coriton O. (2024). Genomic relationships among diploid and polyploid species of the genus Ludwigia L. section Jussiaea using a combination of molecular cytogenetic, morphological, and crossing investigations. BioRxiv, ver. 4 peer-reviewed and recommended  by Peer Community in Evolutionary Biology https://doi.org/10.1101/2023.01.02.522458

te Beest M., Le Roux J.J., Richardson D.M., Brysting A.K., Suda J., Kubešová M., Pyšek P. (2012). The more the better? The role of polyploidy in facilitating plant invasions. Annals of Botany, Volume 109, Issue 1 Pages 19–45, https://doi.org/10.1093/aob/mcr277

Ramsey J. and Ramsey T. S. (2014). Ecological studies of polyploidy in the 100 years following its discovery Phil. Trans. R. Soc. B369 1–20  https://doi.org/10.1098/rstb.2013.0352  

Rice, A., Šmarda, P., Novosolov, M. et al. (2019). The global biogeography of polyploid plants. Nat Ecol Evol 3, 265–273. https://doi.org/10.1038/s41559-018-0787-9

Thouvenot L, Haury J, Thiebaut G. (2013). A success story: Water primroses, aquatic plant pests. Aquat. Conserv. Mar. Freshw. Ecosyst. 23:790–803  https://doi.org/10.1002/aqc.2387  

Spatial genetic structure, i.e. the non-random spatial distribution of genotypes, arises in populations because of different processes including spatially limited dispersal and selection. Knowledge on the spatial genetic structure of plant populations is important to assess biological parameters such as gene dispersal distances and the potential for local adaptations, as well as for applications in conservation management and breeding. In their work, Niskanen and colleagues demonstrate a multifaceted approach to characterise the spatial genetic structure in two replicate sites of a continuously distributed Scots pine population in South-Eastern Finland. They mapped and assessed the ages of 469 naturally regenerated adults and genotyped them using a SNP array which resulted in 157 325 filtered polymorphic SNPs. Their dataset is remarkably powerful because of the large numbers of both individuals and SNPs genotyped. This made it possible to characterise precisely the decay of genetic relatedness between individuals with spatial distance despite the extensive dispersal capacity of Scots pine through pollen, and ensuing expectations of an almost panmictic population.

The authors’ data analysis was particularly thorough. They demonstrated that two metrics of pairwise relatedness, the genomic relationship matrix (GRM, Yang et al. 2011) and the kinship coefficient (Loiselle et al. 1995) were strongly correlated and produced very similar inference of family relationships: >99% of pairs of individuals were unrelated, and the remainder exhibited 2nd (e.g., half-siblings) to 4th degree relatedness. Pairwise relatedness decayed with spatial distance which resulted in extremely weak but statistically significant spatial genetic structure in both sites, quantified as Sp=0.0005 and Sp=0.0008. These estimates are at least an order of magnitude lower than estimates in the literature obtained in more fragmented populations of the same species or in other conifers. Estimates of the neighbourhood size, the effective number of potentially mating individuals belonging to a within-population neighbourhood (Wright 1946), were relatively large with Nb=1680-3210 despite relatively short gene dispersal distances, σg = 36.5–71.3m, which illustrates the high effective density of the population. 

The authors showed the implications of their findings for selection. The capacity for local adaptation depends on dispersal distances and the strength of the selection coefficient. In the study population, the authors inferred that local adaptation can only occur if environmental heterogeneity occurs over a distance larger than approximately one kilometre (or larger, if considering long-distance dispersal). Interestingly, in Scots pine, no local adaptation has been described on similar geographic scales, in contrast to some other European or Mediterranean conifers (Scotti et al. 2023).

The authors’ results are relevant for the management of conservation and breeding. They showed that related individuals occurred within sites only and that they shared a higher number of rare alleles than unrelated ones. Since rare alleles are enriched in new and recessive deleterious variants, selecting related individuals could have negative consequences in breeding programmes. The authors also showed, in their response to reviewers, that their powerful dataset was not suitable to obtain a robust estimate of effective population size, Ne, based on the linkage disequilibrium method (Do et al. 2014). This illustrated that the estimation of Ne used for genetic indicators supported in international conservation policy (Hoban et al. 2020, CBD 2022) remains challenging in large and continuous populations (see also Santo-del-Blanco et al. 2023, Gargiulo et al. 2024).

References

CBD (2022) Kunming-Montreal Global Biodiversity Framework. https://www.cbd.int/doc/decisions/cop-15/cop-15-dec-04-en.pdf

Do C, Waples RS, Peel D, Macbeth GM, Tillett BJ, Ovenden JR (2014). NeEstimator v2: re-implementation of software for the estimation of contemporary effective population size (Ne ) from genetic data. Molecular Ecology Resources 14: 209–214. https://doi.org/10.1111/1755-0998.12157

Gargiulo R, Decroocq V, González-Martínez SC, Paz-Vinas I, Aury JM, Kupin IL, Plomion C, Schmitt S, Scotti I, Heuertz M (2024) Estimation of contemporary effective population size in plant populations: limitations of genomic datasets. Evolutionary Applications, in press, https://doi.org/10.1101/2023.07.18.549323

Hoban S, Bruford M, D’Urban Jackson J, Lopes-Fernandes M, Heuertz M, Hohenlohe PA, Paz-Vinas I, et al. (2020) Genetic diversity targets and indicators in the CBD post-2020 Global Biodiversity Framework must be improved. Biological Conservation 248: 108654. https://doi.org/10.1016/j.biocon.2020.108654

Loiselle BA, Sork VL, Nason J & Graham C (1995) Spatial genetic structure of a tropical understorey shrub, Psychotria officinalis (Rubiaceae). American Journal of Botany 82: 1420–1425. https://doi.org/10.1002/j.1537-2197.1995.tb12679.x

Santos-del-Blanco L, Olsson S, Budde KB, Grivet D, González-Martínez SC, Alía R, Robledo-Arnuncio JJ (2022). On the feasibility of estimating contemporary effective population size (Ne) for genetic conservation and monitoring of forest trees. Biological Conservation 273: 109704. https://doi.org/10.1016/j.biocon.2022.109704

Scotti I, Lalagüe H, Oddou-Muratorio S, Scotti-Saintagne C, Ruiz Daniels R, Grivet D, et al. (2023) Common microgeographical selection patterns revealed in four European conifers. Molecular Ecology 32: 393-411. https://doi.org/10.1111/mec.16750

Wright S (1946) Isolation by distance under diverse systems of mating. Genetics 31: 39–59. https://doi.org/10.1093/genetics/31.1.39

Yang J, Lee SH, Goddard ME & Visscher PM (2011) GCTA: a tool for genome-wide complex trait analysis. The American Journal of Human Genetics 88: 76–82. https://www.cell.com/ajhg/pdf/S0002-9297(10)00598-7.pdf